Essay
GenAI for Good Is Being Built Backwards
Most GenAI for Good projects start from what the technology can do, then find a social problem to fit it. That's the wrong end of the problem. Impact should define the question. GenAI should be the last design decision,
Most GenAI for Good projects start from what the technology can do, then find a social problem to fit it. That’s the wrong end of the problem. Impact should define the question. GenAI should be the last design decision, not the first.
Every major tech conference now has a “GenAI for Good” track. Every foundation has a grant program for it. Every AI lab has a responsible AI division with a slide deck about it. The phrase is everywhere, and it sounds reassuring. It implies direction, ethics, and purpose.
That proliferation is the problem — not the intent behind it.
The intent is genuine. The urgency is real. But when you look closely at how most GenAI for Good projects get built, you find a consistent structural failure: they start from what the technology can do, and only then ask where it might be useful. That sequence feels practical. It is also exactly backwards.
“GenAI for Good” is currently doing the same work that “AI for Good” did before it, and “Tech for Good” did before that. Each wave inherits the same fundamental confusion: the belief that attaching a moral label to a technology category produces meaningful direction.
It isn’t. It’s a starting point at best, and a distraction at worst.
What’s different about GenAI specifically is the scale of the gap between what the technology appears capable of and what it can reliably deliver in high-stakes, under-resourced, and institutionally complex settings. That gap is not just technical. It is organizational, ethical, and political.
That asymmetry matters. A hallucinating model deployed in a commercial chatbot is an embarrassment. A hallucinating model deployed in a healthcare triage tool for a community with limited access to care is a governance failure.